keprep 0.2.2.2

Minimally preprocessing TheBase dMRI data.

KePrep: PreProcessing Strauss Neuroplasticity Brain Bank dMRI data

Overview

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• Free software: MIT license

• Documentation: https://keprep.readthedocs.io.

About

KePrep is a diffusion magnetic resonance imaging (dMRI) preprocessing pipeline designed to provide a reproducible, user-friendly, and easily accessible interface for dMRI data associated with the Strauss Neuroplasticity Brain Bank (SNBB).

Note

The KePrep pipeline uses much of the code from fMRIPrep (Esteban et al., 2019) and QSIPrep (Cieslak et al., 2021) and is built on top of Nipype (Gorgolewski et al., 2011). It is crucial to note that the similarities in the code do not imply that the authors of fMRIPrep, QSIPrep, or Nipype endorse KePrep or its pipeline. These similarities are aimed at providing a consistent format and code for contributing to the pipeline.

dMRI data requires a series of preprocessing steps to be performed before it can be used in further analysis. Although researchers often apply different preprocessing steps using various tools, there is a general consensus on the most common steps. Therefore, KePrep aims to provide a standardized pipeline, allowing researchers to access the dMRI data at different stages of preprocessing.

This pipeline includes the following steps:

1. Denoising

2. Motion and Eddy Current Correction

3. Brain Extraction

4. Bias Field Correction

5. Tractography

6. Coregistration to subject’s anatomical image

While being tailored to the SNBB, KePrep is designed to be easily adaptable to other dMRI datasets.

More information and documentation can be found at https://keprep.readthedocs.io.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.